Fuzzy Clustering Approaches Based on Numerical Optimizations of Modified Objective Functions by Erind Bedalli, Shkelqim Hajrulla, Rexhep Rada, Robert Kosova

“…Fuzzy clustering is a form of unsupervised learning that assigns the elements of a dataset into multiple clusters with varying degrees of membership rather than assigning them to a single cluster. …”
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ADAPTIVE LEARNING OF HIDDEN MARKOV MODELS FOR EMOTIONAL SPEECH by A. V. Tkachenia

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Incremental learning with SVM for multimodal classification of prostatic adenocarcinoma. by José Fernando García Molina, Lei Zheng, Metin Sertdemir, Dietmar J Dinter, Stefan Schönberg, Matthias Rädle

“…The proposed system integrates anatomic, texture, and functional features. The data set was preprocessed using B-Spline interpolation, bias field correction and intensity standardization. …”
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CREATION OF COLLABORATIVE DEVELOPMENT ENVIRONMENT IN THE SYSTEM OF DISTANCE LEARNING by Julia Malieieva, Viktor Kosenko, Olga Malyeyeva, Dmitrij Svetlichnyj

“…At the same time, the following tasks are solved: a review and comparison of existing systems of distance learning; analysis of the functional and features of the Sphere Engine platform; development of the integration algorithm of the service with the system Moodle. …”
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Architectural Synergies in Bi-Modal and Bi-Contrastive Learning by Yujia Gu, Brian Liu, Tianlong Zhang, Xinye Sha, Shiyong Chen

“…Traditionally, such models have been developed independently, using methods like contrastive learning and image-captioning to boost their analytical and creative outputs. …”
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Deep Learning and Its Application in the Field of Rail Transit by XIONG Qunfang, LIN Jun, LIU Yue, YUAN Hao, YOU Jun

“…Additionally, it summarized the main functions and existing problems of deep learning in the field of rail transit, and presented some prospects of future work.…”
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Machine learning for discrimination of phase‐change chalcogenide glasses by Qundao Xu, Meng Xu, Siqi Tang, Shaojie Yuan, Ming Xu, Wei Zhang, Xian‐Bin Li, Zhongrui Wang, Xiangshui Miao, Chengliang Wang, Matthias Wuttig

“…This has led to a dilemma in materials design since an atomistic view of the arrangement in the amorphous state is the key to understanding and optimizing the functionality of these glasses. To tackle this challenge, we present a machine learning (ML) approach to separate electronic phase‐change materials (ePCMs) from other chalcogenides, based upon subtle differences in the short‐range order inside the glassy phase. …”
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LEADING ACTIVITY ALLIVIATING THE PUPILS’ HELPLESSNESS IN LEARNING PROCESS by B. A. Vjatkin, E. S. Davydova, E. V. Zabelina

“…The research novelty implies the investigation of functional correlations between the respondents’ personal helplessness and activity. …”
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Developing Corporate Entrepreneurship by Adopting Learning Practices of Startups by Grażyna Urbanik-Papp

“…The concept of Lean Startup has revolutionized the creation of innovation in startups, as a way of accelerating learning and finding a functioning and profitable business model. …”
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Learning Sejarah Kebudayaan Islam through Google Sites by Muhammad Madarik, Hairul Puadi

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⁠ The Importance of Scientific Integrity for the Improvement of University Level Learning by Iryna Tymchenko, Ihor Danyliuk, Mykola Yaroshov, Roksolana Yaremkevych, Svitlana Demikhova

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An autoencoder learning method for predicting breast cancer subtypes. by Zahra Rostami, Kavitha Mukund, Maryam Masnadi-Shirazi, Shankar Subramaniam

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Accelerating machine learning at the edge with approximate computing on FPGAs by Luis Gerardo León-Vega, Eduardo Salazar-Villalobos, Jorge Castro-Godínez

“… Performing inference of complex machine learning (ML) algorithms at the edge is becoming important to unlink the system functionality from the cloud. …”
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On the added value of sequential deep learning for the upscaling of evapotranspiration by B. Kraft, B. Kraft, B. Kraft, J. A. Nelson, S. Walther, F. Gans, U. Weber, G. Duveiller, M. Reichstein, W. Zhang, M. Rußwurm, D. Tuia, M. Körner, Z. Hamdi, M. Jung

“…Methods based on machine learning (ML) have shown promising results in achieving such upscaling, providing a complementary methodology that is independent from process-based and semi-empirical approaches. …”
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RAFFLE: active learning accelerated interface structure prediction by Ned Thaddeus Taylor, Joe Pitfield, Francis Huw Davies, Steven Paul Hepplestone

“…RAFFLE leverages physical insights and genetic algorithms to intelligently sample configurations, using dynamically evolving 2-, 3-, and 4-body distribution functions as generalised structural descriptors. These descriptors are refined through active learning to guide atom placement strategies. …”
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The Role and Extend of Artificial Intelligence in Enhancing Volleyball Learning by Saif Alaa Naji, Neran Khaleel Abdulqader

“…The results showed that postgraduate students demonstrated a more consistent and logical understanding of AI's educational functions, particularly its flexibility, adaptability, and role in self-directed learning. …”
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Metadig: an application for self-regulated learning in distance education by Beatriz Ortega-Ruipérez

“…Metadig application has been designed and developed to facilitate self-regulated learning through metacognitive strategies in distance higher education teacher training. …”
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Averaged Soft Actor-Critic for Deep Reinforcement Learning by Feng Ding, Guanfeng Ma, Zhikui Chen, Jing Gao, Peng Li

“…The Soft Actor-Critic (SAC) algorithm uses advanced functions to update the policy and value network to alleviate some of these problems. …”
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Exemplary Values of Social Studies Learning in Elementary School by Nur Azizah, Mira, Rika Delima, Adina Sabilah, Mila Karmelia, Sopiah, Safrudin

“…The current state of social studies learning, especially at the elementary level, indicates neglect of local culture, which functions to build student character. …”
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Spike-Based Bayesian-Hebbian Learning of Temporal Sequences. by Philip J Tully, Henrik Lindén, Matthias H Hennig, Anders Lansner

“…Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. …”
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